WO2018221120A1 - Dispositif d'affichage - Google Patents

Dispositif d'affichage Download PDF

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Publication number
WO2018221120A1
WO2018221120A1 PCT/JP2018/017600 JP2018017600W WO2018221120A1 WO 2018221120 A1 WO2018221120 A1 WO 2018221120A1 JP 2018017600 W JP2018017600 W JP 2018017600W WO 2018221120 A1 WO2018221120 A1 WO 2018221120A1
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WO
WIPO (PCT)
Prior art keywords
term
search
page
keyword
terms
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PCT/JP2018/017600
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English (en)
Japanese (ja)
Inventor
潔 関根
Original Assignee
株式会社インタラクティブソリューションズ
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by 株式会社インタラクティブソリューションズ filed Critical 株式会社インタラクティブソリューションズ
Priority to CN201880035833.8A priority Critical patent/CN110678859B/zh
Priority to JP2019522052A priority patent/JP6664784B2/ja
Priority to US16/618,094 priority patent/US20200159801A1/en
Priority to CA3063019A priority patent/CA3063019C/fr
Publication of WO2018221120A1 publication Critical patent/WO2018221120A1/fr
Priority to US18/498,077 priority patent/US20240078276A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/332—Query formulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
    • G06F16/43—Querying
    • G06F16/438—Presentation of query results
    • G06F16/4387—Presentation of query results by the use of playlists
    • G06F16/4393—Multimedia presentations, e.g. slide shows, multimedia albums
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9538—Presentation of query results
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/3332—Query translation
    • G06F16/3334—Selection or weighting of terms from queries, including natural language queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/08—Speech classification or search
    • G10L15/18—Speech classification or search using natural language modelling
    • G10L15/1815—Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/26—Speech to text systems
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/08—Speech classification or search
    • G10L2015/088—Word spotting
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
    • G10L2015/223—Execution procedure of a spoken command

Definitions

  • the present invention relates to a conversation support display device capable of proposing an appropriate presentation page corresponding to a conversation during the conversation.
  • Japanese Patent No. 4551105 discloses a conference support system using voice recognition. Since speech recognition recognizes speech as a sentence, an appropriate slide cannot be read out. Even if an attempt is made to read a slide using only terms recognized by voice recognition, the term does not necessarily match the search term associated with the slide, so the slide cannot be read appropriately.
  • the present invention has an object to provide a presentation system that effectively displays a keyword for selecting the next slide during a presentation.
  • the present invention basically extracts not only the terms included in the conversation but also the terms related to the term, the candidate for the page of the presentation material related to the conversation is extracted. Based on the knowledge that candidates for pages of presentation materials can be proposed appropriately.
  • the present invention relates to a display device including a computer and a portable terminal.
  • This display device can display information for reading a page of presentation material related to conversation.
  • This display device includes a speech recognition unit 53, a conversation-derived term extraction unit 55, a search keyword storage unit 57, a search keyword extraction unit 59, a material storage unit 61, a corresponding page information extraction unit 63, a selected term extraction unit 65, and A selection term display means 71 is provided.
  • the voice recognition means 53 is an element for performing voice recognition.
  • the conversation-derived term extraction means 55 is an element for extracting a plurality of conversation-derived terms from the conversation information recognized by the voice recognition means 53.
  • the search keyword storage means 57 is an element for storing a conversation-derived term and a search keyword in association with each other.
  • the search keyword extraction means 59 is an element for extracting a plurality of search keywords from the search keyword storage means 57 using the plurality of conversation-derived terms extracted by the conversation-derived term extraction means 55.
  • the material storage unit 61 is an element for associating and storing each page of a plurality of presentation materials, a search term of each page, and a score of each search term.
  • the corresponding page information extraction unit 63 is an element for extracting the page of the presentation material related to the search keyword from the material storage unit 59 using the search keyword extracted by the search keyword extraction unit 59 as a search term.
  • the selected term extracting means 65 is an element for extracting a search keyword as a selected term for selecting a slide when a page of the presentation material extracted by the corresponding page information extracting means 63 exists.
  • the selected term display unit 71 is an element for causing the display unit 69 to display the selected term extracted by the selected term extraction unit 65. Since the display device has the above-described means, the selected term can be displayed on the display unit 69.
  • the display device The relevant page information extraction unit 63 uses the search keyword extracted by the search keyword extraction unit 59 as a search term, and the search term having a high score is retrieved from the material storage unit 59 and related to the search keyword. One or a plurality of pages may be extracted.
  • the display device The display unit 69 is a display screen of the terminal,
  • the selected term display unit 71 displays the selected term extracted by the selected term extraction unit 65 in the selected term display area 73 existing at the lower part of the display screen.
  • the display device includes selected term input means 75 for receiving information on selection of the displayed selected term, It may further include page candidate reading means 77 for reading out candidates for pages of a plurality of presentation materials related to the selected term using the selected term input by the selected term input means 75.
  • this display device You may further have the page selection information input means 79 which receives the information from which the page of the specific presentation material was selected among the page candidates of the several presentation material which the page candidate reading means 77 read.
  • the display device can display the page of the selected presentation material on the display unit 69 using the information regarding the page of the presentation material selected by the page selection information input unit 79.
  • the display device Term extracting means 3 for extracting terms in the material that are terms contained in a page of the material; Keyword storage means 5 for storing terms that are keywords related to the terms in the material; Keyword extracting means 7 for extracting a plurality of keywords that are related to the terms in the document from the keyword storage means 5 using the terms in the material extracted by the term extracting means 3; Topics word storage means 9 for storing topics words related to the keywords; Using a plurality of keywords extracted by the keyword extraction means 7, a topic word extraction means 11 for extracting a topic word related to the keyword from the topic word storage means 9; A search term candidate extraction unit 13 for extracting search term candidates on a page of the material from the topic words extracted by the topic word extraction unit 11 and the plurality of keywords extracted by the keyword extraction unit 7; Search term candidate display means 17 for displaying the search term candidates extracted by the search term candidate extraction means 13 on the display unit 15; A search term input means 19 for receiving an input indicating that it is a search term among the search term candidates displayed on the display unit 15; A
  • the present invention provides a computer, Speech recognition means 53 for performing speech recognition; Conversation-derived term extraction means 55 for extracting a plurality of conversation-derived terms from the conversation information recognized by the speech recognition means 53; Search keyword storage means 57 for storing conversation-related terms and search keywords in association with each other; Search keyword extraction means 59 for extracting a plurality of search keywords from the search keyword storage means 57 using a plurality of conversation-derived terms extracted by the conversation-derived term extraction means 55; A material storage unit 61 for storing each page of a plurality of presentation materials, a search term of each page, and a score of each search term in association with each other; Relevant page information extracting means 63 for extracting the page of the presentation material related to the search keyword from the material storage unit 59 using the search keyword extracted by the search keyword extracting means 59 as a search term; A selection term extraction unit 65 that extracts a search keyword as a selection term for selecting a slide when a page of the presentation material extracted by the corresponding page information extraction unit 63 exists; A selected term
  • the present invention can provide a presentation system that effectively displays keywords for selecting the next slide during a presentation.
  • FIG. 1 is a block diagram for explaining a display device of the present invention.
  • FIG. 2 is a block diagram showing the basic configuration of the computer.
  • FIG. 3 is a conceptual diagram showing an example system of the present invention.
  • FIG. 4 is an example of a page with presentation material.
  • FIG. 5 is a conceptual diagram showing a storage example of the keyword storage means.
  • FIG. 6 is a conceptual diagram showing a storage example of the topic word storage means.
  • FIG. 7 is a conceptual diagram showing a storage example of the category word storage means.
  • FIG. 8 is a conceptual diagram showing extracted (category words), topics words, keywords, and terms in the material.
  • FIG. 9 is an example of a display screen.
  • FIG. 10 is a flowchart for explaining an example of use of the retrieval material information storage device of the present invention.
  • FIG. 11 is a conceptual diagram for explaining an example of use of the retrieval material information storage device of the present invention.
  • FIG. 12 is a block diagram for explaining the search material information storage device of the present invention.
  • FIG. 13 is a flowchart for explaining a process example of displaying a selected term and a process of displaying a page of presentation material related to the selected term.
  • FIG. 14 is a conceptual diagram illustrating a display example of the display unit before the selected term is displayed.
  • FIG. 15 is a conceptual diagram illustrating a display example of the display unit when a selected term is displayed.
  • FIG. 16 is a conceptual diagram showing a state in which page candidates are displayed on the display unit.
  • the present invention relates to a display device including a computer and a portable terminal.
  • This display device can display information for reading a page of presentation material related to conversation.
  • FIG. 1 is a block diagram for explaining a display device of the present invention.
  • This device is a computer processing device.
  • the computer may be any one of a portable terminal, a desktop personal computer, and a server, or a combination of two or more. These are usually connected so that information can be exchanged over the Internet (intranet) or the like.
  • the functions may be shared by using a plurality of computers, such as giving some functions to one of the computers.
  • FIG. 2 is a block diagram showing the basic configuration of the computer.
  • the computer has an input unit 31, an output unit 33, a control unit 35, a calculation unit 37, and a storage unit 39, and each element is connected by a bus 41 or the like to exchange information.
  • the control unit may be stored in the storage unit, or various types of information may be stored.
  • the control unit reads a control program stored in the storage unit.
  • a control part reads the information memorize
  • the arithmetic unit performs arithmetic processing using the received various information and stores it in the storage unit.
  • the control unit reads out the calculation result stored in the storage unit and outputs it from the output unit. In this way, various processes are executed. Each means executes these various processes.
  • FIG. 3 is a conceptual diagram showing an example system of the present invention.
  • the system of the present invention (a system including the apparatus of the present invention) includes a portable terminal 45 connected to the Internet or intranet 43 and a server 47 connected to the Internet or intranet 43. It may be. Of course, a single computer or portable terminal may function as the apparatus of the present invention, or a plurality of servers may exist.
  • the monitor or display of the portable terminal 45 may function as the display unit 69.
  • this display device (device of the present invention) includes a speech recognition means 53, a conversation-derived term extraction means 55, a search keyword storage means 57, a search keyword extraction means 59, a material storage section 61, The page information extracting unit 63, the selected term extracting unit 65, and the selected term displaying unit 71 are included.
  • the voice recognition means 53 is an element for performing voice recognition. Speech recognition is well known. In order to perform speech recognition, a microphone that normally collects speech and a speech analysis unit that analyzes speech input from the microphone are included. Speech recognition itself is known as described in Japanese Patent No. 4551105 (Patent Document 1), Japanese Patent No. 6127422, Japanese Patent No. 6114210, and Japanese Patent No. 6107003.
  • the voice recognition means 53 can input the voice included in the conversation and input it to the apparatus, and store the term included in the conversation as data.
  • the voice recognition unit 53 appropriately stores the terms included in the conversation in the storage unit. At this time, the voice recognizing means 53 may store the terminology and information related to the volume or the change in the volume together with the term.
  • the conversation-derived term extraction means 55 is an element for extracting a plurality of conversation-derived terms from the conversation information recognized by the voice recognition means 53. As described above, the terms included in the conversation are appropriately stored in the storage unit.
  • the storage unit stores terms that can be used for searching. This term may be a noun, for example.
  • the storage unit may have a term extraction database storing term extraction terms for extracting terms contained in the conversation according to the use such as medical use and bank use.
  • the conversation-derived term extraction means 55 refers to the term extraction database, reads the term extraction term, and determines whether the term extraction term matches the conversation-derived term stored in the storage unit. You just have to do it.
  • the term for term extraction may be stored in the storage unit as a “conversation-derived term”.
  • the storage unit may also store information on the appearance frequency of the “conversation-derived term” in the conversation for a predetermined period and the volume or change in volume.
  • the term extraction database may store a term extraction term together with a score indicating the ease of becoming a search term for each term.
  • the conversation-derived term extraction means 55 has a “conversation-derived term” with a high score, a “conversation-derived term” with a high frequency, a change in volume (volume increased), a “conversation-derived term”, a score, a frequency, and a volume. Any one or more of these changes may be used as an index to extract a “conversation-derived term” candidate.
  • a coefficient may be stored, and the score of the conversation-derived term may be obtained by multiplying the various coefficients. For example, when the coefficient is 1, there is no change in the score.
  • the score of the conversation-derived term can be adjusted by assigning coefficients from 1.1 to 1.9 according to the degree of the change.
  • the search keyword storage means 57 is an element for storing a conversation-derived term and a search keyword in association with each other.
  • the term derived from conversation is basically a term assumed to be included in a conversation (for example, a conversation between a sales person and a customer).
  • the search keyword storage means 57 stores the conversation-derived term and the search keyword in association with each other, and converts it into a search keyword that is a term suitable for the search.
  • the search keyword storage means 57 may be achieved by a storage unit (storage device), or may be achieved by a database and a database management system.
  • storage device memorize
  • the storage device may record a score for use in a search in association with the search keyword.
  • conversation-derived terms are “can thin”, “thin”, and “slim”, and examples of search keywords corresponding thereto are “slimming”, “obesity”, “body type”, and “physical examination”.
  • the search keyword extraction means 59 is an element for extracting a plurality of search keywords from the search keyword storage means 57 using a plurality of conversation-derived terms extracted by the conversation-derived term extraction means 55.
  • Search keyword extraction means 59 extracts search keywords stored in association with conversation-derived terms in search keyword storage means 57 for each of a plurality of conversation-derived terms. At this time, the score stored together with the search keyword may be extracted. Then, the search keyword extracting means 59 stores the extracted search keyword (and score) in the storage unit. Then, for all (or a predetermined number) of conversation-derived terms, search keywords (and scores) are extracted from the search keyword storage means 57 and stored in the storage unit.
  • the search keyword extraction means 59 extracts a search keyword using the search keyword (and its score) temporarily stored in the storage unit. At this time, the search keyword extraction means 59 may extract the search keyword having a high score. The search keyword extraction means 59 stores the extracted search keyword in the storage unit. At this time, the search keyword extracting means 59 may store a plurality of search keywords and respective scores together.
  • the material storage unit 61 is an element for associating and storing each page of a plurality of presentation materials, a search term of each page, and a score of each search term.
  • the corresponding page information extraction unit 63 is an element for extracting the page of the presentation material related to the search keyword from the material storage unit 59 using the search keyword extracted by the search keyword extraction unit 59 as a search term.
  • Each page of the presentation material related to the search term is stored in the material storage unit 61 (for example, along with the score and ranking).
  • the corresponding page information extraction means 63 obtains information for extracting each page of the presentation material having a high score or ranking from the material storage unit 61 using the search keyword.
  • the relevant page information extraction unit 63 uses the search keyword extracted by the search keyword extraction unit 59 as a search term, and the search term having a high score is retrieved from the material storage unit 59 and related to the search keyword.
  • One or a plurality of pages may be extracted.
  • the selected term extraction unit 65 is an element for extracting a search keyword as a selected term for selecting a slide when a page of the presentation material extracted by the corresponding page information extraction unit 63 exists. There may be one or more selected terms.
  • the search term may be a predetermined number, for example, three, four, five, or six. The number of search terms may be determined using the size of the area where the selected term is displayed in the display unit, the size of the character of the selected term, and the number of characters of the selected term. In this case, for example, the selected term extraction unit 65 obtains information on the length of the area where the selected term is displayed. Next, the selected term extraction unit 65 obtains information regarding the size of the character in the portion where the selected term is displayed on the display unit.
  • the selected term extraction means 65 obtains information on the size other than the character portion per one when displaying the selected term.
  • the selected term extraction means 65 extracts, for example, one selected term having a high priority due to a high score or ranking, and the number of selected terms is one, two, three, four, five,
  • the selected term is displayed as in the case of six cases, the length of the selected term portion displayed on the display unit is obtained, and the length of the selected term portion and the length of the portion where the selected term is displayed are obtained. Compare Then, when the length of the selected term portion is shorter than the display portion, one selected term is added. In this way, the selected term extraction means 65 can extract an appropriate number of selected terms.
  • the selected term display unit 71 is an element for causing the display unit 69 to display the selected term extracted by the selected term extraction unit 65.
  • the selected term can be displayed on the display unit 69.
  • FIG. 13 is a flowchart for explaining an example of a process of displaying a selected term and a page of a presentation material related to the selected term.
  • S means a step.
  • the person in charge who owns the display device described above has a conversation with the customer (conversation start: S01). Then, the voice recognizing means 53 recognizes information related to the conversation including the terms included in the conversation (voice recognition step: S02). Information (including terms) on the speech-recognized conversation is appropriately stored in the storage unit.
  • the display device stores coefficients related to speech changes such as frequency of terms at a given time, volume increase / decrease when a term is uttered, and change in voice wavelength, and analyzes conversation-related information. At this time, a predetermined coefficient may be read in association with the term.
  • the conversation-derived term extraction unit 55 appropriately reads information on the conversation recognized by the voice recognition unit 53 from the storage unit, and extracts a plurality of conversation-derived terms using the read information (conversation-derived term extraction step: S03).
  • the display device has a database relating to conversation-derived terms, and by referring to the database, it is possible to select terms that are nouns or effective for retrieval from terms included in the conversation. In this way, conversation-derived terms are extracted.
  • the score of the conversation-derived term may be stored in association with the conversation-derived term in consideration of the possibility of being used for the search.
  • the search keyword storage means 57 stores conversation-derived terms and search keywords in association with each other. At this time, the search keyword may be stored in association with the search keyword score in consideration of the possibility of being used for the search.
  • the search keyword extraction unit 59 extracts a plurality of search keywords from the search keyword storage unit 57 using the plurality of conversation-derived terms extracted by the conversation-derived term extraction unit 55 (read appropriately from the storage unit) (search). Keyword extraction step: S04). In this way, instead of conversation-derived terms (the conversation-derived terms may be search keywords as they are), the search is performed by converting to search keywords, so that the appropriate presentation material page can be searched.
  • the material storage unit 61 stores each page of a plurality of presentation materials, the search term of each page, and the score of each search term in association with each other. Then, the corresponding page information extracting means 63 uses the search keyword extracted by the search keyword extracting means 59 as a search term to extract the page of the presentation material related to the search keyword from the material storage unit 59 (page extraction). Step: S05).
  • the presentation material pages do not need to be displayed at this stage, and there are one or more related presentation material pages, and information for reading the related pages (for example, information on the material ID and the number of pages) is provided. Extract it. Information for reading out the extracted related pages is stored in the storage unit as appropriate.
  • the relevant page information extraction unit 63 uses the search keyword extracted by the search keyword extraction unit 59 as a search term, and the search term having a high score is retrieved from the material storage unit 59 and related to the search keyword. One or a plurality of pages may be extracted.
  • the selected term extracting unit 65 determines whether or not the page of the presentation material extracted by the corresponding page information extracting unit 63 exists, and if it exists, the selected keyword for selecting the slide as the search keyword. (Selected term extraction step: S06). Note that the search keyword may be extracted as a selected term as it is. The extracted selected terms are stored in the storage unit as appropriate.
  • the selected term display unit 71 displays the selected term extracted by the selected term extraction unit 65 (read out from the storage unit as appropriate) on the display unit 69 (selected term display step: S07).
  • FIG. 14 is a conceptual diagram illustrating a display example of the display unit before the selected term is displayed.
  • FIG. 15 is a conceptual diagram showing a display example of the display unit when the selected term is displayed. In this example, the selected term is displayed in the selected term display area 73 present at the bottom of the display screen.
  • the display unit is a touch panel type, and a plurality of selected terms (five in this example) are displayed in the selected term display area 73. In this way, the selected term is displayed on the display unit.
  • the person in charge touches one of the selected terms displayed on the touch panel (or if the display unit is a desktop computer monitor, the selected term is selected with the cursor moved by a mouse etc.) )
  • the selected term input means 75 inputs information in which a specific selected term is selected into the display device, and the display device receives this input information (selected information input step: S08). Information regarding the input specific selected term is appropriately stored in the storage unit.
  • FIG. 16 is a conceptual diagram showing a state in which page candidates are displayed on the display unit.
  • the lower part of the selected term display area 73 or the selected term display area 73 moves upward, and the presentation is displayed below the selected term display area 73. It may be displayed in a state in which a plurality of candidates for the page of the material are reduced in size. Note that this page candidate display step may be skipped.
  • the display unit When the display unit is a touch panel, the person in charge (user) presses the upper part of the iconized page candidate. Then, the display device grasps that a specific candidate has been selected. That is, the page selection information input unit 79 receives information in which a page of a specific presentation material is selected from a plurality of presentation material page candidates read by the page candidate reading unit 77. Then, the received information is input to the display device.
  • the input information (information on selection of a specific page or information on the specified page) is appropriately stored in the storage unit.
  • the display device displays information about the page of the presentation material selected by the page selection information input means 79 (read out from the storage unit as appropriate) and displays the page of the selected presentation material on the display unit 69 ( Page display step: S10).
  • the display device Term extracting means 3 for extracting terms in the material that are terms contained in a page of the material; Keyword storage means 5 for storing terms that are keywords related to the terms in the material; Keyword extracting means 7 for extracting a plurality of keywords that are related to the terms in the document from the keyword storage means 5 using the terms in the material extracted by the term extracting means 3; Topics word storage means 9 for storing topics words related to the keywords; Using a plurality of keywords extracted by the keyword extraction means 7, a topic word extraction means 11 for extracting a topic word related to the keyword from the topic word storage means 9; A search term candidate extraction unit 13 for extracting search term candidates on a page of the material from the topic words extracted by the topic word extraction unit 11 and the plurality of keywords extracted by the keyword extraction unit 7; Search term candidate display means 17 for displaying the search term candidates extracted by the search term candidate extraction means 13 on the display unit 15; A search term input means 19 for receiving an input indicating that it is a search term among the search term candidates displayed on the display unit 15; A
  • the retrieval material information storage device includes a term extraction means 3, a keyword storage means 5, a keyword extraction means 7, a topic word storage means 9, a topic word extraction means 11, and a search term.
  • a keyword extraction means 3 a keyword storage means 5, a keyword extraction means 7, a topic word storage means 9, a topic word extraction means 11, and a search term.
  • Candidate extraction means 13, search term candidate display means 17, search term input means 19, and material search information storage means 21 are included.
  • Each means is a means by a computer, and each process is achieved by cooperation of hardware and software.
  • the term extraction means 3 is a means for extracting terms in the material that are terms contained in a certain page of the material.
  • materials are so-called presentation materials.
  • the format of the presentation material is not particularly limited.
  • Examples of presentation software include Microsoft (registered trademark) PowerPoint (registered trademark), King Soft (registered trademark) King Soft Office (registered trademark), Apache (registered trademark) Open Office Impress (registered trademark), Keynote (registered trademark) ), Lotus Freelance (registered trademark), Illustrator (registered trademark), PDF (registered trademark) and Pretzie (registered trademark).
  • Examples of materials are materials created by any of these presentation software, for example.
  • the presentation software is software that can display the contents of each page on a display unit such as a screen.
  • Fig. 4 shows an example of a page with presentation materials.
  • the presentation material includes a plurality of texts input by the creator.
  • the user can visually recognize a plurality of characters.
  • the computer stores information such as text input by the user and input information related to the text (character size, character color, presence / absence of animation) together with the text.
  • a preferable example of the term extracting means 3 is to give a text evaluation (score) according to input information (text size, character color, presence / absence of animation) related to the text when extracting the text. . For example, the larger the character, the more often it indicates the content of the presentation material, so a higher score is given.
  • the term extraction means 3 stores an evaluation (score) on the effect related to the text, reads out the term as a text-related score when extracting the term, and calculates other scores when calculating a score to be described later. Evaluation may be performed by addition or multiplication.
  • the term extraction means 3 itself is known.
  • the presentation material has a plurality of text information.
  • the presentation material is stored in, for example, a server (or in a computer) storage unit.
  • the term extraction means 3 reads each page of the stored presentation material and reads the text included in each page. Then, the term extraction means 3 analyzes the part of speech of the read text.
  • a part of speech database exists in the storage unit, and various terms and parts of speech are stored.
  • scores as search terms for various terms may be stored together depending on the application.
  • the term extraction means 3 extracts terms (especially nouns) included in the text, and extracts one or more terms in the material using the frequency and the term scores stored in the storage unit. do it.
  • the term extraction means 3 extracts the terms A, B and C from a certain page, the term C appears twice, the terms A and B appear once, and the term A stored in the storage unit.
  • the term extracting means 3 may extract the terms C and B as terms in the material. Then, the terms in the extracted material (terms C and B) are stored in the storage unit in association with information about the page from which the page can be read. Then, the terms C and B can be read out together with the page.
  • Another example of the term extracting means 3 is to identify a portion where the largest font is used in a page of a presentation. A predetermined coefficient is given to the term in the material included in the portion where the largest font is used.
  • the coefficient (first coefficient: a 1 ) only needs to be stored in the storage unit.
  • the term extraction means 3 stores the first coefficient in the storage unit together with the term in the material included in the portion where the largest font is used. Further, the term extracting means 3 may store a coefficient (second coefficient: a 2 ) corresponding to the font size together with the term in the material in the storage unit.
  • the keyword storage means 5 is a means for storing a term that becomes a keyword related to the term in the material.
  • the keyword storage unit 5 may be realized by a storage unit and an element (for example, a control program) for reading information from the storage unit.
  • the keyword is a term for making it easy to search each page by using not only a term in a plurality of materials but also a related term as a search term when searching each page. As a result, the search terms stored in association with each page are reduced, and the search can be performed quickly.
  • the terms in the material may be keywords.
  • the keyword can be said to be the first conversion word related to the term in the material.
  • a keyword may be a term selected from a plurality of types of terms in a document and suitable for use in a search.
  • Terms in the material are terms included in the presentation. For this reason, the terms in the document may not necessarily match the search terms or may not be suitable as search terms.
  • the term ob gene or ob / ob mouse is included in the presentation. This is associated with obesity genes (and obesity, obesity experimental animals).
  • the keyword storage means 5 stores the obesity genes (and obesity and obesity experimental animals) that are the keywords in association with the ob genes and ob / ob mice that are the terms in the material.
  • the search terms stored in association with each page are unified terms. For this reason, when a search is performed, a related page can be read quickly.
  • FIG. 5 is a conceptual diagram showing a storage example of the keyword storage means.
  • the keyword storage means stores one or a plurality of keywords in association with each of the plurality of terms in the material, and calculates a score (this score is b 1 ) for each keyword. It is associated and remembered. It is preferable that this score is input in advance so as to be higher for a term suitable for a search.
  • the keyword extraction means 7 is a means for extracting a plurality of keywords that are related to the terms in the material from the keyword storage means 5 using the terms in the material extracted by the term extraction means 3.
  • the keyword storage means 5 stores terms that become keywords in association with the terms in the material. For this reason, the keyword extraction means 7 can read the term used as the keyword relevant to the term in a material from the keyword memory
  • multiple terms are extracted from a page. For this reason, a plurality of terms that are keywords for a certain page are usually extracted. Also, there are usually multiple terms that are keywords related to the terms in the material (scores may be assigned to each). For this reason, a plurality of terms that are keywords for a certain page are usually extracted.
  • the keyword extraction means 7 may evaluate the score of each keyword using the coefficient of the term in the material and the keyword score stored in the storage unit.
  • An example of the keyword score is a 1 ⁇ a 2 ⁇ b 1 .
  • the control unit reads out the control program and also reads out each coefficient and score stored in the storage unit. Thus, it is only necessary to cause the calculation unit to perform calculation for obtaining a 1 ⁇ a 2 ⁇ b 1 and to store the calculation result in the storage unit.
  • the storage unit stores the appearance frequency of the term in the material (this coefficient is a 21 ) and an addition coefficient (this coefficient is a 22 ) when a specific keyword is extracted from a plurality of types of material terms.
  • the keyword score may be obtained by storing a 1 ⁇ a 2 ⁇ a 21 ⁇ a 22 ⁇ b 1 and stored in the storage unit.
  • a strong coefficient may be given to the emphasis color included in a certain page. In this case, it has means for analyzing the color of the term from the page and a storage unit for storing the coefficient for each color, and if the coefficient for the color is read from the storage unit using the color of the analyzed term. Good.
  • coefficients and scores are stored for various elements, read out, and multiplied or added to obtain the scores. You can find superior candidates by memorizing and comparing word scores.
  • the topic word storage means 9 is a means for storing the topic words related to the keyword.
  • the topic word storage unit 9 may be realized by a storage unit and an element (for example, a control program) for reading information from the storage unit.
  • the topic word storage means may store the topic word “obesity” in association with keywords of obesity genes, obesity, and obesity experimental animals.
  • the topic word may be a term in which a plurality of keywords are further unified or a generalized term. By using topic words, the search can be performed more quickly. Examples of topic words are disease names, drug names, active ingredient names, and pharmaceutical company names. That is, the topic word can be said to be the second conversion word related to the term in the material.
  • the topic word may be a term in which a term suitable for use in a search is assigned to a plurality of types of keywords. Further, the topic language may relate to a message.
  • the topic word extraction unit 11 is a unit for extracting a topic word related to the keyword from the topic word storage unit 9 using a plurality of keywords extracted by the keyword extraction unit 7.
  • the topic word storage means 9 stores topic words related to the keyword. Therefore, the topic word extraction unit 11 extracts a topic word related to the keyword from the topic word storage unit 9 using the plurality of keywords extracted by the keyword extraction unit 7.
  • FIG. 6 is a conceptual diagram showing a storage example of the topic word storage means.
  • the topic word storage means stores one or a plurality of topic words in association with each of a plurality of keywords, and stores a score associated with each topic word. It is preferable that this score is input in advance so as to be higher for a term suitable for a search.
  • the search term candidate extraction means 13 is a means for extracting search term candidates on a page of the material from the topic words extracted by the topic word extraction means 11 and a plurality of keywords extracted by the keyword extraction means 7.
  • one or more topic words that are related to a certain page are stored in one or more storage units.
  • a plurality of keywords that are related to a certain page are stored. For example, if the control program performs control such that all the topic words are candidates for search terms and several keywords (for example, four in consideration of the size displayed on the display unit), the search terms are candidates.
  • the term candidate extraction unit 13 sets all the read topic words as search term candidates, and sets four of the keywords as search term candidates.
  • the keyword storage means 5 may store a plurality of keywords and the scores of the keywords in association with each other, and the keyword extraction means 7 may extract the scores of the keywords together with the keywords. .
  • a keyword with a high score is extracted as a search term candidate.
  • the topic word storage means 9 stores the topic words and the scores of the respective topic words in association with each other, and the topic word extraction means 11 has a predetermined number (1) having a high score among the plurality of keywords extracted by the keyword extraction means 7. Or two or more) may be used as topic word influential candidates, and topic words related to a predetermined number (one or more) of topic word influential candidates may be extracted from the topic word storage means 9.
  • the above search information storage device is Furthermore, you may have the category word memory
  • the category word storage means 25 is a means for storing category words related to topics words.
  • the category word extraction means 27 is a means for extracting a category word related to the topic word from the category word storage means 25 using the topic word extracted by the topic word extraction means 11.
  • the category word can be said to be the third conversion word related to the term in the document.
  • the category word may be a term selected from a plurality of types of topic words suitable for use in category search. Examples of categorical words may indicate subjects that are considered interested in the material.
  • FIG. 7 is a conceptual diagram showing a storage example of the category word storage means.
  • the category word storage means stores one or more category words in association with each of a plurality of topic words, and stores a score in association with each category word. It is preferable that this score is input in advance so as to be higher for a term suitable for a search.
  • FIG. 8 is a conceptual diagram showing extracted (category words), topic words, keywords, and terms in the material.
  • the search term candidate extraction unit 13 may extract a predetermined number (one or two or more) having a high score among the plurality of keywords extracted by the keyword extraction unit 7 as search term candidates. Further, the search term candidate extraction unit 13 extracts a predetermined number (one or two or more) of search terms from the topic words extracted by the topic word extraction unit 11 using the keyword score and the topic word score. You may do.
  • the topic word storage means 9 stores the topic words and the scores of the respective topic words in association with each other.
  • the keyword storage means 5 stores a plurality of keywords and the score of each keyword in association with each other. A certain topic word has an original keyword. That is, topics words are read using keywords. Topics words are always associated with one or more keywords.
  • the search term candidate extraction unit 13 reads a score related to a topic word from the topic word storage unit 9 and also reads a score of each keyword from which the topic word is extracted from the keyword storage unit 5. Then, for example, when there are a plurality of keywords for a certain topic word, the search term candidate extraction means 13 causes the calculation unit to sum the score of each keyword and the topic word score and the keyword score (or the keyword sum) Multiply score). In this way, the score after aggregation relating to the topic words is obtained and stored in the storage unit.
  • the search term candidate extraction unit 13 reads the score after aggregation for a plurality of topic words, compares the score with a calculation unit, and extracts a predetermined number (one or more) of topic words. In this way, even when the number of topic words to be extracted is determined, the search term candidate extraction means 13 can extract a predetermined number of topic words.
  • the search term candidate display means 17 is a means for causing the display unit 15 to display the search term candidates extracted by the search term candidate extraction means 13.
  • Search term candidate display means 17 The display unit 15 searches for a predetermined number (one or two or more) of keywords extracted as search term candidates and a predetermined number (one or two or more) of topic words extracted as search term candidates.
  • a candidate for terms Of the plurality of keywords extracted by the keyword extraction means 7, those not extracted as search term candidates and the topic words extracted by the topic word extraction means 11 that are not extracted as search term candidates are used as search terms.
  • the search term input means 19 When an input indicating that a search term preliminary candidate is used as a search term is received, the preliminary search term candidate is set as a search term. What is displayed as a search term candidate may be used as a search term except for a case where an input indicating that it is not a search term is received.
  • the material search information storage means 21 is a means for storing the search term input by the search term input means 19 and information related to a page with the material in association with each other.
  • the apparatus of the present invention may further display content type candidates according to the type of presentation material, and store the content type in association with each page of the presentation (or the presentation itself).
  • the apparatus of the present invention reads a presentation format (Powerpoint (registered trademark), PDF (registered trademark), Word (registered trademark), etc.) stored in the storage unit.
  • the apparatus of the present invention reads text included in the read format.
  • the apparatus of the present invention includes a content analysis term database that stores content analysis terms.
  • the apparatus of the present invention analyzes the content type using terms stored in the term database for content analysis. For example, if the material is PDF (registered trademark) and the text “attached document” exists relatively first, “attached document” is extracted as a candidate for the content type of the material. Then, “attached document” is displayed as a content type on the display unit, and when an approval is input from the user, “attached document” is stored with respect to the content type in association with the material.
  • Fig. 9 shows an example of the display screen.
  • a page with presentation material is displayed in the upper half of the display screen.
  • search term candidates each search term candidate is displayed together with an icon (check box) that is adopted or not adopted.
  • the search term candidates are arranged in the order of category words, topics words, and keywords from the left. Terms in the document may also be displayed on the display unit.
  • the adoption check box is marked.
  • the device 1 that has received the input from the computer stores the page associated with the presentation in association with the approved search terms (and the score of each search term) in the storage unit.
  • the search term input means 19 is a means for receiving an input indicating that it is a search term among the search term candidates displayed on the display unit 15.
  • the input by the check box functions as the search term input means 19.
  • the user inputs to reject a search term candidate that is in an adopted state, for example, a mark is input to a check box that is not adopted.
  • the device 1 that has received the non-adopted input from the check box sets the instructed search term candidate to the non-adopted state.
  • the search term candidate is not adopted.
  • the apparatus 1 may store search term candidates that have been rejected as a search term related to the above page after lowering the score (for example, by halving the score).
  • the search term candidate extraction means 13 does not extract as search terms
  • the check boxes for not adopting are marked (or none of the check boxes are marked).
  • a mark is entered in the adoption check box.
  • the device 1 that has received the input of adoption from the check box adopts the designated search term candidate.
  • search term candidates are adopted. That is, the search term is stored in association with the page as a search term for a certain page. At this time, since the search term is selected by the user, the search term may be stored in a state where the score is added or multiplied.
  • FIG. 10 is a flowchart for explaining an example of use of the retrieval material information storage device of the present invention. That is, this figure is a diagram for explaining a retrieval material information storage method using the retrieval material information storage device.
  • S means a step (process).
  • the user's terminal or computer stores the presentation material in the storage unit (or the storage unit of the server).
  • the device 1 extracts a term in the material, which is a term included in the page, for each page of the presentation material (S102). At this time, the device 1 may give a score to the term in the material. For example, if terms in a document appear frequently, or if accompanied by bold, colored characters, animations, etc., register points in advance and assign a score to the terms in the document using the registered point information. Also good.
  • the device 1 has a dictionary of terms in the material, and the dictionary stores various terms in the material in association with the terms in the material and the score. The device 1 stores the terms in the material. The score may be read out.
  • the score of the term in the document may be obtained using the score of the term in the document existing in the dictionary and the score related to the added points (for example, addition or multiplication). In this case, if the number of terms in the document is set in advance, the one with the highest score may be used as the term in the document.
  • the apparatus 1 extracts a plurality of keywords that are related to the term in the material from the storage unit using the extracted one or more terms in the material (S103).
  • the storage unit records terms that are keywords related to the terms in the material. For this reason, the apparatus 1 can extract the keyword relevant to it from a memory
  • a score as a search term may be given to each keyword.
  • a score related to the high frequency of the keyword may be registered, the score corresponding to the number of times the keyword is duplicated may be read, and added or multiplied with the score. In this way, a plurality of keywords (and the score of each keyword) are obtained.
  • the apparatus 1 may extract a category word related to the topic word from the storage unit using the extracted topic word (S105). This step is an optional step.
  • the device 1 extracts a search term candidate for a page with a document from topics words and a plurality of keywords (and category words) (S106).
  • the device 1 stores in advance control commands for extracting search term candidates, and in accordance with the control commands, searches for candidate search terms on a page with a document from topics words and a plurality of keywords (and category words). Extract it.
  • An example of the control command is that four high scores among a plurality of keywords and two high topic words (and all category words) are extracted as search term candidates. In this way, search term candidates for pages with presentation materials are automatically extracted.
  • the storage unit may store extracted search term candidates as search terms for a certain page.
  • the apparatus 1 may display the extracted search term candidate on the display unit (S107).
  • the presentation target page (which is made smaller), topics words that are not candidates for the search terms, and a plurality of keywords (and category words) may be displayed together on the display unit. In this case, the user can select a search term.
  • the terminal receives an input related to the approval, and the search term candidates extracted by the device 1 are stored as they are in the storage unit as the search terms related to the page with the presentation material (S111). .
  • the search term that reflects these corrections Candidates are used as search terms related to pages in the storage unit (S121).
  • the terminal receives input related to the approval, and the corrected search term candidate is stored in the storage unit as a search term related to a page of the presentation material. (S122).
  • Term extraction means 3 which extracts a term in the document, which is a term included in the page with the document, Keyword storage means 5 for storing a term that becomes a keyword related to the term in the document 5, Keyword extraction means 7 for extracting a plurality of keywords that are related to the terms in the material from the keyword storage means 5 using the terms in the material extracted by the term extraction means 3; Topics word storage means 9 for storing topics words related to the keywords, A topic word extraction unit 11 that extracts a topic word related to the keyword from the topic word storage unit 9 using a plurality of keywords extracted by the keyword extraction unit 7; A search term candidate extraction unit 13 for extracting a search term candidate on a page having a document from the topic word extracted by the topic word extraction unit 11 and the plurality of keywords extracted by the keyword extraction unit 7; Search term candidate display means 17 for displaying the search term candidates extracted by the search term candidate extraction means 13 on the display unit 15;
  • the search term input means 19 which receives input indicating that it is a search term among the search term candidates displayed on the
  • FIG. 11 is a conceptual diagram (block diagram) for explaining an example of use of the retrieval material information storage device of the present invention.
  • the basic database (DB) includes a content DB, a customer DB, a log DB, and a DB that stores other information.
  • These databases are connected to an engine called an interactive pro framework through an interface.
  • This engine can exchange information with various terminals (for example, a PC tablet, a mobile terminal, and a mobile phone) via an application programming interface (API).
  • the engine can exchange information with control programs and applications in the client, HTML data, moving image data, power point data, PDF data, document data, and database management software.
  • This engine is synchronized with the server (cloud) so that information can be exchanged.
  • information can be exchanged with various databases and software including BI (business intelligence), CRM (customer relationship management), and DWH (data warehouse) via the server.
  • BI business intelligence
  • CRM customer relationship management
  • DWH data warehouse
  • the present invention provides a computer, Speech recognition means 53 for performing speech recognition; Conversation-derived term extraction means 55 for extracting a plurality of conversation-derived terms from the conversation information recognized by the speech recognition means 53; Search keyword storage means 57 for storing conversation-related terms and search keywords in association with each other; Search keyword extraction means 59 for extracting a plurality of search keywords from the search keyword storage means 57 using a plurality of conversation-derived terms extracted by the conversation-derived term extraction means 55; A material storage unit 61 for storing each page of a plurality of presentation materials, a search term of each page, and a score of each search term in association with each other; Relevant page information extracting means 63 for extracting the page of the presentation material related to the search keyword from the material storage unit 59 using the search keyword extracted by the search keyword extracting means 59 as a search term; A selection term extraction unit 65 that extracts a search keyword as a selection term for selecting a slide when a page of the presentation material extracted by the corresponding page information extraction unit 63 exists; A selected term
  • the present invention can be used in the display terminal industry, information and communication industry, software development, pharmaceutical industry, financial industry, and the like.

Abstract

La présente invention a pour objet de fournir un système de présentation permettant d'afficher efficacement un mot-clé pour effectuer la sélection de la diapositive suivante au cours d'une présentation. À cet effet, l'invention porte sur un dispositif d'affichage comprenant : un moyen de reconnaissance vocale (53) ; un moyen d'extraction de terme dérivé de conversation (55); un moyen de stockage de mot-clé de recherche (57) ; un moyen d'extraction de mot-clé de recherche (59) ; une unité de stockage de matériau (61); un moyen d'extraction d'informations de page pertinentes (63) ; un moyen d'extraction de terme de sélection (65) ; et un moyen d'affichage de terme de sélection (71).
PCT/JP2018/017600 2017-06-01 2018-05-07 Dispositif d'affichage WO2018221120A1 (fr)

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US16/618,094 US20200159801A1 (en) 2017-06-01 2018-05-07 Display Device
CA3063019A CA3063019C (fr) 2017-06-01 2018-05-07 Systeme de presentation d'assistance parlee
US18/498,077 US20240078276A1 (en) 2017-06-01 2023-10-31 Display Device Displaying a Keyword for Selecting a Next Slide During Presentation

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WO2020153111A1 (fr) * 2019-01-25 2020-07-30 株式会社インタラクティブソリューションズ Système d'aide à la présentation
JP2020119399A (ja) * 2019-01-25 2020-08-06 株式会社インタラクティブソリューションズ プレゼンテーション支援システム
CN111902831A (zh) * 2019-01-25 2020-11-06 互动解决方案公司 演示支援系统
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CN114175148A (zh) * 2020-04-24 2022-03-11 互动解决方案公司 语音分析系统
CN114175148B (zh) * 2020-04-24 2023-05-12 互动解决方案公司 语音分析系统
JP2021012700A (ja) * 2020-08-06 2021-02-04 株式会社インタラクティブソリューションズ プレゼンテーション支援システム

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CN110678859B (zh) 2020-11-24
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US20200159801A1 (en) 2020-05-21
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